Data Scientist

Vintti is a staffing agency dedicated to boosting the economic efficiency of US companies. We provide access to a diverse range of skilled Latin American professionals, allowing businesses to build robust teams without the traditional high costs associated with domestic hiring. Our model supports companies in maximizing their resources, driving innovation, and achieving sustainable growth.

A Data Scientist plays a crucial role in interpreting and managing massive sets of data to help organizations make data-driven decisions. They use a mix of statistical analysis, machine learning, and predictive modeling to identify trends, patterns, and insights. By transforming raw data into actionable insights, Data Scientists enable businesses to optimize operations, create strategic plans, and improve outcomes. Their expertise in coding, algorithms, and data visualization allows them to solve complex problems and communicate their findings effectively to stakeholders across various departments.

- Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field
- Master’s or Ph.D. in a relevant field is preferred
- Proven experience as a Data Scientist
- Proficiency in programming languages such as Python, R, or SQL
- Strong knowledge of statistical techniques, machine learning algorithms, and data modeling
- Experience with data visualization tools like Tableau, Power BI, or matplotlib
- Familiarity with distributed data/computing tools such as Hadoop, Spark, and Hive
- Hands-on experience with data preprocessing, transformation, and feature engineering
- Demonstrated ability to design and implement machine learning models
- Experience with cloud platforms like AWS, GCP, or Azure
- Strong understanding of data warehousing and ETL processes
- Proficiency in conducting hypothesis tests and A/B testing
- Strong problem-solving skills and attention to detail
- Excellent communication skills, both written and verbal
- Ability to work collaboratively in a cross-functional team environment
- Knowledge of software development practices, including version control (Git)
- Ability to mentor junior team members and conduct code reviews
- Familiarity with agile development methodologies
- Strong organizational and time-management skills
- Ability to stay current with the latest trends and best practices in data science

- Collect, clean, and preprocess large datasets from various sources.
- Design and implement data models and algorithms to drive business solutions.
- Analyze data using statistical techniques and provide actionable insights.
- Visualize data using tools such as Tableau, Power BI, or matplotlib.
- Collaborate with cross-functional teams to understand their data needs and provide solutions.
- Develop and maintain machine learning models to improve decision-making processes.
- Conduct hypothesis testing and perform A/B testing to validate assumptions.
- Document and present technical findings to both technical and non-technical stakeholders.
- Continuously explore new data sources and techniques to improve data quality and efficiency.
- Implement and monitor data pipelines to ensure data integrity and availability.
- Stay up-to-date with the latest data science trends, tools, and best practices.
- Debug and troubleshoot data-related issues and improve system performance.
- Deploy and maintain scalable and reliable data infrastructure.
- Mentor junior team members and share knowledge within the team.
- Participate in code reviews to ensure adherence to best practices and coding standards.

The ideal candidate for the Data Scientist role will possess a strong educational background with a Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field, and a Master’s or Ph.D. is preferred. They will have proven experience as a Data Scientist, demonstrating proficiency in programming languages such as Python, R, or SQL, and an in-depth knowledge of statistical techniques, machine learning algorithms, and data modeling. This candidate will be adept at data visualization using tools like Tableau, Power BI, or matplotlib and have hands-on experience with distributed data/computing tools such as Hadoop, Spark, and Hive. They will excel in data preprocessing, transformation, and feature engineering, with a demonstrated ability to design and implement machine learning models. Experience with cloud platforms like AWS, GCP, or Azure, as well as a solid understanding of data warehousing and ETL processes, will be essential. The ideal candidate will be skilled in hypothesis testing and A/B testing, with strong problem-solving skills, attention to detail, and excellent communication abilities. They will exhibit a proactive and self-motivated attitude towards continuous learning and improvement, coupled with the ability to mentor junior team members and conduct code reviews. Familiarity with agile development methodologies and software development practices, including version control (Git), will be crucial. They will be a strong team player with exceptional organizational and time-management skills, able to thrive in a fast-paced, dynamic work environment. Additionally, the ideal candidate will demonstrate strong ethical standards concerning data privacy and security, an analytical mindset, creativity in solving complex business problems, and resilience in troubleshooting and resolving data-related challenges. Their ability to communicate complex technical concepts clearly to non-technical stakeholders and their enthusiasm for discovering insights in data will set them apart, making them a valuable asset to our team.

- Collect, clean, and preprocess large datasets from various sources.
- Design and implement data models and algorithms to drive business solutions.
- Analyze data using statistical techniques and provide actionable insights.
- Visualize data using tools such as Tableau, Power BI, or matplotlib.
- Collaborate with cross-functional teams to understand their data needs and provide solutions.
- Develop and maintain machine learning models to improve decision-making processes.
- Conduct hypothesis testing and perform A/B testing to validate assumptions.
- Document and present technical findings to both technical and non-technical stakeholders.
- Continuously explore new data sources and techniques to improve data quality and efficiency.
- Implement and monitor data pipelines to ensure data integrity and availability.
- Stay up-to-date with the latest data science trends, tools, and best practices.
- Debug and troubleshoot data-related issues and improve system performance.
- Deploy and maintain scalable and reliable data infrastructure.
- Mentor junior team members and share knowledge within the team.
- Participate in code reviews to ensure adherence to best practices and coding standards.

- Analytical mindset with strong problem-solving abilities
- Detail-oriented approach with a focus on accuracy and data quality
- Proactive and self-motivated attitude towards continuous learning and improvement
- Strong interpersonal skills for effective collaboration with cross-functional teams
- Ability to communicate complex technical concepts clearly to non-technical stakeholders
- High level of curiosity and enthusiasm for discovering insights in data
- Flexibility to adapt to changing priorities and project requirements
- Strong organizational skills and ability to manage multiple tasks simultaneously
- Resilience and perseverance to troubleshoot and resolve data-related challenges
- Creative thinking to develop innovative solutions for complex business problems
- Demonstrated leadership skills and ability to mentor and guide junior team members
- Commitment to maintaining high standards of coding and data management practices
- Strong ethical standards, particularly concerning data privacy and security
- Team player mindset with a willingness to share knowledge and support peers
- Ability to thrive in a fast-paced, dynamic work environment

- Competitive salary range based on experience and qualifications
- Comprehensive health, dental, and vision insurance
- 401(k) plan with company matching
- Generous paid time off, including vacation, holidays, and personal days
- Flexible work hours and remote work options
- Professional development opportunities, including conferences and workshops
- Tuition reimbursement for relevant courses and certifications
- Wellness programs and gym membership discounts
- Employee assistance program for mental health and wellness support
- Opportunities for career advancement and internal promotions
- Collaborative and inclusive company culture
- Cutting-edge technology and tools provided
- Casual dress code and comfortable work environment
- Regular team-building activities and social events
- Onsite snacks and beverages (if applicable)
- Commuter benefits or transportation reimbursement
- Paid parental leave and support for new parents